
Improving AttentionBased Handwritten Mathematical Expression Recognition with Scale Augmentation and Drop Attention
Handwritten mathematical expression recognition (HMER) is an important r...
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Joint MultiDimension Pruning
We present joint multidimension pruning (named as JointPruning), a new ...
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Robust 3D Selfportraits in Seconds
In this paper, we propose an efficient method for robust 3D selfportrai...
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PolyFit: Polynomialbased Indexing Approach for Fast Approximate Range Aggregate Queries
Range aggregate queries find frequent application in data analytics. In ...
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RCCDualGAN: An Efficient Approach for Outlier Detection with Few Identified Anomalies
Outlier detection is an important task in data mining and many technolog...
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Long ShortTerm Sample Distillation
In the past decade, there has been substantial progress at training incr...
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Learning From Brains How to Regularize Machines
Despite impressive performance on numerous visual tasks, Convolutional N...
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Prioraware Neural Network for PartiallySupervised MultiOrgan Segmentation
Accurate multiorgan abdominal CT segmentation is essential to many clin...
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CircConv: A Structured Convolution with Low Complexity
Deep neural networks (DNNs), especially deep convolutional neural networ...
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ERNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs
Recurrent Neural Networks (RNNs) are becoming increasingly important for...
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Generative Adversarial Active Learning for Unsupervised Outlier Detection
Outlier detection is an important topic in machine learning and has been...
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A Unified Analysis of Stochastic Momentum Methods for Deep Learning
Stochastic momentum methods have been widely adopted in training deep ne...
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EIGEN: EcologicallyInspired GENetic Approach for Neural Network Structure Searching
Designing the structure of neural networks is considered one of the most...
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An Aggressive Genetic Programming Approach for Searching Neural Network Structure Under Computational Constraints
Recently, there emerged revived interests of designing automatic program...
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Towards BudgetDriven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing
Recently, Deep Convolutional Neural Network (DCNN) has achieved tremendo...
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Learning Topics using Semantic Locality
The topic modeling discovers the latent topic probability of the given t...
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Efficient Recurrent Neural Networks using Structured Matrices in FPGAs
Recurrent Neural Networks (RNNs) are becoming increasingly important for...
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C3PO: Database and Benchmark for Earlystage Malicious Activity Detection in 3D Printing
Increasing malicious users have sought practices to leverage 3D printing...
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CLSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs
Recently, significant accuracy improvement has been achieved for acousti...
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A Framework in CRM Customer Lifecycle: Identify Downward Trend and Potential Issues Detection
Customer retention is one of the primary goals in the area of customer r...
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Towards UltraHigh Performance and Energy Efficiency of Deep Learning Systems: An AlgorithmHardware CoOptimization Framework
Hardware accelerations of deep learning systems have been extensively in...
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Image Dataset for Visual Objects Classification in 3D Printing
The rapid development in additive manufacturing (AM), also known as 3D p...
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An Area and Energy Efficient Design of DomainWall MemoryBased Deep Convolutional Neural Networks using Stochastic Computing
With recent trend of wearable devices and Internet of Things (IoTs), it ...
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Evaluate the Malignancy of Pulmonary Nodules Using the 3D Deep Leaky Noisyor Network
Automatic diagnosing lung cancer from Computed Tomography (CT) scans inv...
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Thoracic Disease Identification and Localization with Limited Supervision
Accurate identification and localization of abnormalities from radiology...
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A Simple Analysis for Expconcave Empirical Minimization with Arbitrary Convex Regularizer
In this paper, we present a simple analysis of fast rates with high pr...
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CirCNN: Accelerating and Compressing Deep Neural Networks Using BlockCirculantWeight Matrices
Largescale deep neural networks (DNNs) are both compute and memory inte...
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SEPNets: Small and Effective Pattern Networks
While going deeper has been witnessed to improve the performance of conv...
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HardwareDriven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks
Recently, Deep Convolutional Neural Networks (DCNNs) have made unprecede...
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Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Recently low displacement rank (LDR) matrices, or socalled structured m...
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SCDCNN: HighlyScalable Deep Convolutional Neural Network using Stochastic Computing
With recent advancing of Internet of Things (IoTs), it becomes very attr...
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Unified Convergence Analysis of Stochastic Momentum Methods for Convex and Nonconvex Optimization
Recently, stochastic momentum methods have been widely adopted in train...
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Improved Dropout for Shallow and Deep Learning
Dropout has been witnessed with great success in training deep neural ne...
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